charts and price charts, where we depict low- and high-volatility assets with distinct trends. We find that varying the scale … riskiness of an asset even if the underlying volatility is the same. Furthermore, past returns predict future return …

bonds) and analyze their multi-scaling properties by estimating the parameters of a Markov-switching multifractal model (MSM …) with Lognormal volatility components. In order to see how well estimated models capture the temporal dependency of the … general, the Lognormal MSM models generate "apparent" long memory in good agreement with empirical scaling provided one uses …

fractal power laws and scaling will be explained. The main part focuses on the estimation of the tail index as a scaling …

The creation and scaling of startups are inherently linked to risk-taking, with various types of owners handling these … regarding research and scaling. It outlines conditions under which VCbacked startups prefer riskier, yet potentially more …

Guttman (1947) developed a scaling method in which the items measuring an attribute can be ordered according to the … strength of the attribute. The Guttman scaling model assumes that every member of the population belongs to a scale type and … contingency tables, pi-star can be applied to latent class models, including scaling models for dichotomous data. This study …

for scaling up existing estimates of ecosystem service values to larger geographical scales. It also presents a case study …

is based on the assumption that national context matters. We argue that the chances for scaling local experiments between … the strengths and weaknesses of their climate policies. Second, we assess the scaling potential of local experiments, in … analyze actual scaling between the two German cities, which share the same national context. More generally, we explore how …